Table  and Fig. REF  present the quantitative and qualitative results of state-of-art methods on the NOCS dataset respectively. The comparison points include learning-based methods relying on a category-level prior, such as NOCS [1]}, KeypointNet [2]}, and 6-PACK with or without temporal prediction [3]}. These methods are offline trained on both real and synthetic training sets, which are rendered with 3D object models extracted from the same categories of ShapeNetCore [4]}.
In contrast, ICP [5]}, MaskFusion [6]}, TEASER++* [7]} and the proposed BundleTrack have no access to any training data based on 3D models.
